用股票的Shapley值作为系统风险

IF 5.7 Q1 BUSINESS, FINANCE
Haim Shalit
{"title":"用股票的Shapley值作为系统风险","authors":"Haim Shalit","doi":"10.1108/jrf-08-2019-0149","DOIUrl":null,"url":null,"abstract":"This study aims to propose the Shapley value that originates from the game theory to quantify the relative risk of a security in an optimal portfolio.,Systematic risk as expressed by the relative covariance of stock returns to market returns is an essential measure in pricing risky securities. Although very much in use, the concept has become marginalized in recent years because of the difficulties that arise estimating beta. The idea is that portfolios can be viewed as cooperative games played by assets aiming at minimizing risk. With the Shapley value, investors can calculate the exact contribution of each risky asset to the joint payoff. For a portfolio of three stocks, this study exemplifies the Shapley value when risk is minimized regardless of portfolio return.,This study computes the Shapley value of stocks and indices for optimal mean-variance portfolios by using daily returns for the years 2016–2019. This results in the risk attributes allocated to securities in optimal portfolios. The Shapley values are analyzed and compared to the standard beta estimates to determine the ranking of assets with respect to pertinent risk and return.,An alternative approach to value risk and return in optimal portfolios is presented in this study. The logic and the mechanics of Shapley value theory in portfolio analysis have been explained, and its advantages relative to standard beta analysis are presented. Hence, financial analysts when adding or removing specific assets from present positions will have the true and exact impact of their actions by using the Shapley value instead of the beta.,When computing the Shapley value, portfolio risk is decomposed exactly among its assets because it considers all possible coalitions of portfolios. In that sense, financial analysts when adding or removing specific securities from present holdings will be able to predict the true and exact impact of their transactions by using the Shapley value instead of the beta. The main implication for investors is that risk is ultimately priced relative to their holdings. This prevents the subjective mispricing of securities, as standard beta is not used and might allow investors to gain from arbitrage conditions.,The logic and the methodology of Shapley value theory in portfolio analysis have been explained as an alternative to value risk and return in optimal portfolios by presenting its advantages relative to standard beta analysis. The conclusion is that the Shapley value theory contributes much more financial optimization than to standard systematic risk analysis because it enables looking at the contribution of each security to all possible coalitions of portfolios.","PeriodicalId":46579,"journal":{"name":"Journal of Risk Finance","volume":"21 1","pages":"459-468"},"PeriodicalIF":5.7000,"publicationDate":"2020-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1108/jrf-08-2019-0149","citationCount":"2","resultStr":"{\"title\":\"Using the Shapley value of stocks as systematic risk\",\"authors\":\"Haim Shalit\",\"doi\":\"10.1108/jrf-08-2019-0149\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study aims to propose the Shapley value that originates from the game theory to quantify the relative risk of a security in an optimal portfolio.,Systematic risk as expressed by the relative covariance of stock returns to market returns is an essential measure in pricing risky securities. Although very much in use, the concept has become marginalized in recent years because of the difficulties that arise estimating beta. The idea is that portfolios can be viewed as cooperative games played by assets aiming at minimizing risk. With the Shapley value, investors can calculate the exact contribution of each risky asset to the joint payoff. For a portfolio of three stocks, this study exemplifies the Shapley value when risk is minimized regardless of portfolio return.,This study computes the Shapley value of stocks and indices for optimal mean-variance portfolios by using daily returns for the years 2016–2019. This results in the risk attributes allocated to securities in optimal portfolios. The Shapley values are analyzed and compared to the standard beta estimates to determine the ranking of assets with respect to pertinent risk and return.,An alternative approach to value risk and return in optimal portfolios is presented in this study. The logic and the mechanics of Shapley value theory in portfolio analysis have been explained, and its advantages relative to standard beta analysis are presented. Hence, financial analysts when adding or removing specific assets from present positions will have the true and exact impact of their actions by using the Shapley value instead of the beta.,When computing the Shapley value, portfolio risk is decomposed exactly among its assets because it considers all possible coalitions of portfolios. In that sense, financial analysts when adding or removing specific securities from present holdings will be able to predict the true and exact impact of their transactions by using the Shapley value instead of the beta. The main implication for investors is that risk is ultimately priced relative to their holdings. This prevents the subjective mispricing of securities, as standard beta is not used and might allow investors to gain from arbitrage conditions.,The logic and the methodology of Shapley value theory in portfolio analysis have been explained as an alternative to value risk and return in optimal portfolios by presenting its advantages relative to standard beta analysis. The conclusion is that the Shapley value theory contributes much more financial optimization than to standard systematic risk analysis because it enables looking at the contribution of each security to all possible coalitions of portfolios.\",\"PeriodicalId\":46579,\"journal\":{\"name\":\"Journal of Risk Finance\",\"volume\":\"21 1\",\"pages\":\"459-468\"},\"PeriodicalIF\":5.7000,\"publicationDate\":\"2020-10-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1108/jrf-08-2019-0149\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Risk Finance\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1108/jrf-08-2019-0149\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BUSINESS, FINANCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Risk Finance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/jrf-08-2019-0149","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 2

摘要

本研究旨在提出源自博弈论的Shapley值,以量化最优投资组合中证券的相对风险。,由股票回报率与市场回报率的相对协方差表示的系统风险是风险证券定价的一个重要指标。尽管这个概念在使用中非常多,但近年来由于估计贝塔值的困难,这个概念已经被边缘化了。其理念是,投资组合可以被视为资产之间的合作游戏,旨在将风险降至最低。通过Shapley值,投资者可以计算出每种风险资产对联合收益的确切贡献。对于三只股票的投资组合,本研究举例说明了当风险最小化而不考虑投资组合回报时的Shapley值。,本研究通过使用2016年至2019年的每日回报率,计算股票和指数的Shapley值,以获得最佳平均方差投资组合。这导致风险属性被分配给最佳投资组合中的证券。分析Shapley值并将其与标准贝塔估计进行比较,以确定资产在相关风险和回报方面的排名。,本文提出了一种在最优投资组合中评估风险和回报的替代方法。解释了Shapley价值理论在投资组合分析中的逻辑和机制,并介绍了其相对于标准贝塔分析的优势。因此,金融分析师在将特定资产从当前头寸中添加或移除时,将通过使用Shapley值而不是β,对其行为产生真实而准确的影响。,在计算Shapley值时,投资组合风险在其资产中准确分解,因为它考虑了所有可能的投资组合联盟。从这个意义上说,金融分析师在增加或从当前持有的特定证券时,将能够通过使用Shapley值而不是贝塔值来预测其交易的真实和准确影响。对投资者来说,主要的含义是风险最终是相对于他们的持股定价的。这防止了证券的主观错误定价,因为没有使用标准贝塔,可能会让投资者从套利条件中获利。,Shapley价值理论在投资组合分析中的逻辑和方法已被解释为最佳投资组合中价值风险和回报的替代方案,通过展示其相对于标准贝塔分析的优势。结论是,Shapley价值理论对财务优化的贡献远大于标准的系统风险分析,因为它能够观察每种证券对所有可能的投资组合联盟的贡献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using the Shapley value of stocks as systematic risk
This study aims to propose the Shapley value that originates from the game theory to quantify the relative risk of a security in an optimal portfolio.,Systematic risk as expressed by the relative covariance of stock returns to market returns is an essential measure in pricing risky securities. Although very much in use, the concept has become marginalized in recent years because of the difficulties that arise estimating beta. The idea is that portfolios can be viewed as cooperative games played by assets aiming at minimizing risk. With the Shapley value, investors can calculate the exact contribution of each risky asset to the joint payoff. For a portfolio of three stocks, this study exemplifies the Shapley value when risk is minimized regardless of portfolio return.,This study computes the Shapley value of stocks and indices for optimal mean-variance portfolios by using daily returns for the years 2016–2019. This results in the risk attributes allocated to securities in optimal portfolios. The Shapley values are analyzed and compared to the standard beta estimates to determine the ranking of assets with respect to pertinent risk and return.,An alternative approach to value risk and return in optimal portfolios is presented in this study. The logic and the mechanics of Shapley value theory in portfolio analysis have been explained, and its advantages relative to standard beta analysis are presented. Hence, financial analysts when adding or removing specific assets from present positions will have the true and exact impact of their actions by using the Shapley value instead of the beta.,When computing the Shapley value, portfolio risk is decomposed exactly among its assets because it considers all possible coalitions of portfolios. In that sense, financial analysts when adding or removing specific securities from present holdings will be able to predict the true and exact impact of their transactions by using the Shapley value instead of the beta. The main implication for investors is that risk is ultimately priced relative to their holdings. This prevents the subjective mispricing of securities, as standard beta is not used and might allow investors to gain from arbitrage conditions.,The logic and the methodology of Shapley value theory in portfolio analysis have been explained as an alternative to value risk and return in optimal portfolios by presenting its advantages relative to standard beta analysis. The conclusion is that the Shapley value theory contributes much more financial optimization than to standard systematic risk analysis because it enables looking at the contribution of each security to all possible coalitions of portfolios.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Journal of Risk Finance
Journal of Risk Finance BUSINESS, FINANCE-
CiteScore
6.20
自引率
6.70%
发文量
37
期刊介绍: The Journal of Risk Finance provides a rigorous forum for the publication of high quality peer-reviewed theoretical and empirical research articles, by both academic and industry experts, related to financial risks and risk management. Articles, including review articles, empirical and conceptual, which display thoughtful, accurate research and be rigorous in all regards, are most welcome on the following topics: -Securitization; derivatives and structured financial products -Financial risk management -Regulation of risk management -Risk and corporate governance -Liability management -Systemic risk -Cryptocurrency and risk management -Credit arbitrage methods -Corporate social responsibility and risk management -Enterprise risk management -FinTech and risk -Insurtech -Regtech -Blockchain and risk -Climate change and risk
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信